David Paulus , Gerdien de Vries , Marijn Janssen , Bartel Van de Walle
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引用次数: 1
Abstract
The complex and uncertain environment of the humanitarian response to crises can lead to data bias, which can affect decision-making. Evidence of data bias in crisis information management (CIM) remains scattered despite its potentially significant impact on crisis response. To understand what biases emerge in complex crises and how they affect CIM, we conducted a combined interview and document analysis study. Focusing on the largest humanitarian crisis in the world, i.e., the conflict in Yemen, we conducted 25 interviews with managers and analysts of response organizations, and assessed 47 reports and datasets created by response organizations in Yemen. We find evidence of a cycle of bias reinforcement through which bias cascades between field, headquarters and donor levels of crisis response. Researchers, as well as practitioners, need to consider these underlying biases and reinforcement loops because they influence what data can be collected when, by whom, from whom, and how the data is shared and used. To the CIM literature, we contribute an in-depth understanding of how four types of data bias emerge in crises: political, accessibility, topical, and sampling bias.
期刊介绍:
The International Journal of Information Management (IJIM) is a distinguished, international, and peer-reviewed journal dedicated to providing its readers with top-notch analysis and discussions within the evolving field of information management. Key features of the journal include:
Comprehensive Coverage:
IJIM keeps readers informed with major papers, reports, and reviews.
Topical Relevance:
The journal remains current and relevant through Viewpoint articles and regular features like Research Notes, Case Studies, and a Reviews section, ensuring readers are updated on contemporary issues.
Focus on Quality:
IJIM prioritizes high-quality papers that address contemporary issues in information management.